Quick Start

Get up and running with Atulya in 60 seconds.

Start the API Server

pip (API only)

pip install atulya-api
export OPENAI_API_KEY=sk-xxx
export ATULYA_API_LLM_API_KEY=$OPENAI_API_KEY

atulya-api

API available at http://localhost:8888

Docker (Full Experience)

export OPENAI_API_KEY=sk-xxx

docker run --rm -it --pull always -p 8888:8888 -p 9999:9999 \
  -e ATULYA_API_LLM_API_KEY=$OPENAI_API_KEY \
  -v $HOME/.atulya-docker:/home/atulya/.pg0 \
  ghcr.io/eight-atulya/atulya:latest

• API: http://localhost:8888
• Control Plane (Web UI): http://localhost:9999

LLM Provider

Atulya requires an LLM with structured output support. Recommended: Groq with gpt-oss-20b for fast, cost-effective inference. See LLM Providers for more details.

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Use the Client

Python

pip install atulya-client

from atulya_client import Atulya

client = Atulya(base_url="http://localhost:8888")

# Retain: Store information
client.retain(bank_id="my-bank", content="Alice works at Google as a software engineer")

# Recall: Search memories
client.recall(bank_id="my-bank", query="What does Alice do?")

# Reflect: Generate disposition-aware response
client.reflect(bank_id="my-bank", query="Tell me about Alice")

Node.js

npm install @eight-atulya/atulya-client

import { AtulyaClient } from '@eight-atulya/atulya-client';

const client = new AtulyaClient({ baseUrl: 'http://localhost:8888' });

// Retain: Store information
await client.retain('my-bank', 'Alice works at Google as a software engineer');

// Recall: Search memories
await client.recall('my-bank', 'What does Alice do?');

// Reflect: Generate response
await client.reflect('my-bank', 'Tell me about Alice');

CLI

curl -fsSL https://atulya.eightengine.com/get-cli | bash

# Retain: Store information
atulya memory retain my-bank "Alice works at Google as a software engineer"

# Recall: Search memories
atulya memory recall my-bank "What does Alice do?"

# Reflect: Generate response
atulya memory reflect my-bank "Tell me about Alice"

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What's Happening

Operation	What it does
Retain	Content is processed, facts are extracted, entities are identified and linked in a knowledge graph
Recall	Four search strategies (semantic, keyword, graph, temporal) run in parallel to find relevant memories
Reflect	Retrieved memories are used to generate a disposition-aware response

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Next Steps

• Retain — Advanced options for storing memories
• Recall — Search and retrieval strategies
• Reflect — Disposition-aware reasoning
• Memory Banks — Configure disposition and background
• Server Deployment — Docker Compose, Helm, and production setup